Triple
T15248155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gotanda |
E364439
|
entity |
| Predicate | nearbyArea |
P2064
|
FINISHED |
| Object | Osaki |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Osaki | Statement: [Gotanda, nearbyArea, Osaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osaki Context triple: [Gotanda, nearbyArea, Osaki]
-
A.
Osaki City
Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
-
B.
Kaizuka
Kaizuka is a coastal city in Osaka Prefecture, Japan, known for its historical temples, traditional festivals, and proximity to Osaka Bay.
-
C.
Osaki New City
chosen
Osaki New City is a major business and commercial district in Tokyo known for its modern office complexes, high-rise buildings, and urban redevelopment projects.
-
D.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
E.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f4f9d48190b96a7e0c6993cd69 |
completed | April 15, 2026, 9:49 p.m. |
Created at: April 10, 2026, 3:13 a.m.